Driessen Samuel's Library tagged IT → View Popular

None of these claims is ridiculous. Each of them, in fact, has a lot of merit. But how many of them have lasting merit?
So based in part on what I’ve learned about electrification, here’s are my predictions about the move by businesses to cloud computing: It’s going to be a long transition, but an inexorable one.

09 Sep 09

Why corporate IT should unchain our office computers. - By Farhad Manjoo - Slate Magazine

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security socialmedia IT

12 Aug 09

Google, WalMart, and MyBarackObama.com: The Power of the Real Time Enterprise - O'Reilly Radar

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web2.0 enterprise2.0 IT

infused with IT i
As I said in my keynote at the Web 2.0 Expo NY (and in a followup radar post), WalMart is a better example of Enterprise 2.0 than any of these more trendy examples of user contribution systems.
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- If Google's key innovation with PageRank was to recognize that a link was a vote, which could be counted and measured to get better search results, so too, WalMart recognized early on that a purchase was a vote.
- competitive advantage comes from capturing data more quickly, and building systems to respond automatically to that data.
- Sensing, processing, and responding (based on pre-built models of what matters, "the database of expectations," so to speak) is arg
- hybrid human-machine system
- What became clear in the ensuing decade is that humans are not just part of the programming, but also sensors and actuators for computers. Our aggregate behavior is measured, monitored, and becomes feedback that improves the overall intelligence of the system. That is why I've said that the defining characteristic of Web 2.0 applications is that they "harness collective intelligence."
- Aside: I seem to have lost the battle to define Web 2.0 as" the use of the network as platform to build systems that get better the more people use them. Perhaps its the lure of the obvious: companies and products that harness explicit user contribution are easier to recognize than those that pursue the more subtle and difficult task of harnessing implicit contribution. Or perhaps it's the persistent gravitational tug of the idea that the heart of Web 2.0 is ad-supported business models; therefore, enterprise features that look like those of well-known companies featuring user contribution and ad-supported business models must by definition also be "2.0." For me, the far more profound and powerful systems come from harnessing both explicit and implicit human contribution.

06 Aug 09

When Information is NOT the Answer : Andrew McAfee’s Blog

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informationarchitecture IT knowledgemanagement cio

IT’s ability to provide needed information to business decision makers
What type of supporting data do we need to make sense of a rapidly changing market? What other information is required to support execution? What organizational, behavioral, and cultural changes will we need to capture the benefits of improved information?
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- These companies track fashion globally, spot emerging trends, and translate them into new products
- demands good information,
- Zara succeeds in large part because the company makes comparatively light use of market data and sales information, at least as these terms are commonly understood in the retailing industry.
- combining it with other hopefully relevant information
- Each retailer forecasts differently, of course, but I find their techniques broadly similar: they all gather lots of data, analyze it centrally, then use the resulting predictions to determine shipments to stores. In this model, the stores themselves have fairly limited roles: they are expected to record data accurately and send it promptly, then do their best to sell whatever headquarters decides to send them.
- But Zara, operating in an intensely turbulent environment, does something totally different. The company doesn’t really generate a store-level sales forecast at all. Instead, it relies on its store managers to tell headquarters what they think they could sell immediately at their locations. Headquarters then gets as many of these clothes as possible to the stores as quickly as possible.
- They rely largely on intuition and experience, on walking the floor and talking to customers and employees.
- Information technology is still critically important at Zara. The company uses technology to present store managers with a multimedia digital order form, and to transmit completed forms back to headquarters. IT is used heavily to support execution, in short, but not at all to assist with data-based analysis or decision making about getting the right clothes into stores at the right time.
- ‘data vacuum’ – a lack of aggregated, filtered, and massaged information from throughout the corporation
- As I wrote here, Zara believes that the relevant knowledge for fast fashion forecasting isn’t general knowledge (the kind that can be digitized), it’s specific knowledge (the kind that can’t)
- Zara spends almost no time on store-level sales forecasting and other similar kinds of data analysis. Second, it has moved decision making down very low in the organization, because this is where the relevant knowledge is. And third, it gives these decision makers very little market data or other forms of general knowledge.
- For this decision, what’s the relevant knowledge? What’s the mix of specific knowledge and general knowledge required to make this decision well?
- that executives will assume that all or most of the relevant knowledge will be general knowledge